The posting
Company description Publicis Groupe is not just a company you work for; it’s a platform for you to take your talent to the world. If you want to help change the world, ideas alone are not enough. Real impact can only come from having meaningful access to a world of knowledge, people and resources. At Publicis Groupe, you are connected to our global network, intelligence, tools, clients, brands and 80,000 brilliant minds with expertise in data, technology, media, strategy, creativity and business transformation, all literally at your fingertips. Go ahead, the world is waiting. Publicis Groupe is the third largest communications group in the world. Founded in Paris in 1926, we are present in more than 100 countries as leaders in marketing, communication, and digital business transformation. Two of its biggest solution hubs in Singapore - Publicis Communications and Publicis Media & Digital. Publicis Communications, the creative communications hub of the Publicis Groupe, is a collective of the most passionate, purposeful, and progressive creative agencies in Singapore. They are Publicis Worldwide, Leo Burnett, Saatchi & Saatchi, Prodigious, and MSL. Publicis Media & Digital, which is comprised of global media agency brands Starcom, Zenith, Spark Foundry, and Performics, is powered by digital-first, data-driven global practices that together, help our clients navigate the modern media landscape. Our two other solution hubs, Publicis Sapient and Publicis Commerce, empower businesses to embrace digital transformation and equip them with a total commerce experience. Overview As a Junior Commerce Data Analyst, you will support the connection of commerce data sources into our agency tool, where commerce solutions, dashboards and measurement outputs are housed. You will help ensure data is accurate, usable and clearly translated for local markets, supporting campaign measurement, marketplace performance tracking and commerce decision-making across key retail media platforms. You will work closely with commerce, product, data and engineering teams to turn data into practical insights, clear reporting and measurable business impact. This role is best suited to someone who is curious, structured and detail-oriented, with an interest in commerce, data and AI-enabled solutions. The ideal candidate does not need deep technical experience, but should be comfortable asking questions, checking data accuracy and translating numbers into simple, practical outputs for teams. Responsibilities Support the setup, mapping and maintenance of commerce data feeds from marketplaces, content and campaign platforms into tools, working with data and engineering teams to ensure the right inputs are available for commerce solutions. Produce and maintain commerce performance dashboards, experiment tracking, product-feature reporting and solution-usage reports to surface actionable insights. Support A/B test analysis, uplift measurement and pre/post campaign comparisons to evaluate product, media and commerce solution changes. Translate data into clear recommendations and prioritised next steps for product, growth and strategy teams. Collaborate with commerce, product, engineering and data teams to operationalise metrics, validate data quality, document data definitions and enable reproducible analyses. Support ad-hoc and recurring analyses to measure business impact and inform roadmap decisions. Document methods, assumptions and results; present findings to stakeholders in concise, non-technical terms. Qualifications At least 1 year of experience, or a recent graduate in statistics, economics, data science, business analytics, computer science, marketing analytics or a related field (Prior internship or project work involving A/B testing, analytics or dashboarding) Strong foundation in SQL for data querying. Basic understanding of data pipelines, APIs, data connectors or ETL concepts is a plus; hands-on expertise is not required, but the candidate should be comfortable learning how data moves between systems. Basic understanding of AI/ML concepts and model evaluation (exposure to predictive models or experimentation is a plus). Proficiency in data visualization (Tableau, Looker, Power BI, or similar) and ability to define clear KPIs. Strong analytical thinking, attention to detail and ability to communicate insights clearly and comfortable working with cross-functional teams and learning fast in a product-focused environment. Exposure to tools or data sources such as Excel or Google Sheets, SQL databases, dashboarding tools, marketplace seller centres, retail media platforms, Google Analytics, platform exports or campaign reports is helpful. Experience with Python/R for analysis, or familiarity with experiment platforms and feature-flagging systems will be a plus. Basic understanding of commerce measurement metrics such as GMV, conversion rate, ROAS, basket size, traffic, affiliate contribution, content performance and marketplace campaign performance is a plus.
